Fairness through unawareness is the process of learning a predictor that does not explicitly use sensitive attributes in the prediction process. However, dropping the sensitive attributes is not sufficient to remove discrimination as it can be highly predictable implicitly from other features. It has been shown  [1]}, [2]}, [3]}, [4]} that discrimination highly occurs in different systems such as housing, criminal justice, and education that do not explicitly depend on sensitive attributes in their predictions.
